{"id":8493,"date":"2024-06-06T23:01:01","date_gmt":"2024-06-06T15:01:01","guid":{"rendered":""},"modified":"2024-06-06T23:01:01","modified_gmt":"2024-06-06T15:01:01","slug":"\u56fe\u50cf\u8d28\u91cf\u8bc4\u4f30\u7b97\u6cd5_\u8bc4\u4ef7\u56fe\u50cf\u8d28\u91cf\u7684\u4e09\u8981\u7d20","status":"publish","type":"post","link":"https:\/\/mushiming.com\/8493.html","title":{"rendered":"\u56fe\u50cf\u8d28\u91cf\u8bc4\u4f30\u7b97\u6cd5_\u8bc4\u4ef7\u56fe\u50cf\u8d28\u91cf\u7684\u4e09\u8981\u7d20"},"content":{"rendered":"

\u4e00\u3001\u6982\u8ff0<\/strong><\/h2>\n

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 <\/p>\n

\u56fe\u50cf\u8d28\u91cf\u7684\u4e3b\u89c2\u8bc4\u4ef7<\/h3>\n

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\u7edd\u5bf9\u8bc4\u4ef7<\/h4>\n

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\"\u56fe\u50cf\u8d28\u91cf\u8bc4\u4f30\u7b97\u6cd5_\u8bc4\u4ef7\u56fe\u50cf\u8d28\u91cf\u7684\u4e09\u8981\u7d20<\/p>\n

\u76f8\u5bf9\u8bc4\u4ef7<\/h4>\n

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\"\u56fe\u50cf\u8d28\u91cf\u8bc4\u4f30\u7b97\u6cd5_\u8bc4\u4ef7\u56fe\u50cf\u8d28\u91cf\u7684\u4e09\u8981\u7d20<\/p>\n

 <\/p>\n

\u56fe\u50cf\u8d28\u91cf\u5ba2\u89c2\u8bc4\u4ef7<\/h3>\n

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\"\u56fe\u50cf\u8d28\u91cf\u8bc4\u4f30\u7b97\u6cd5_\u8bc4\u4ef7\u56fe\u50cf\u8d28\u91cf\u7684\u4e09\u8981\u7d20<\/p>\n

Imatest\u548cDxO analyzer\u6709\u5f02\u66f2\u540c\u5de5\u4e4b\u5904\uff0c\u90fd\u662f\u5c06\u5f71\u50cf\u8d28\u91cf\u8bc4\u6d4b\u62c6\u5206\u6210\u591a\u4e2a\u6d4b\u8bd5\u9879\u76ee\uff0c\u5206\u522b\u5bf9\u6bcf\u4e2a\u9879\u76ee\u8fdb\u884c\u6d4b\u8bd5\u3001\u6253\u5206\u3002\u4e24\u8005\u76f8\u6bd4\uff0cDxO analyzer\u7684\u6d4b\u8bd5\u9879\u76ee\u4f1a\u7a0d\u5fae\u5168\u9762\u4e00\u4e9b\u3002<\/p>\n

\u65e0\u8bba\u662fImatest\u8fd8\u662fDxO analyzer\uff0c\u4e24\u4e2a\u6d4b\u8bd5\u7cfb\u7edf\u90fd\u662f\u901a\u8fc7\u201c\u6d4b\u8bd5\u5361+\u5149\u6e90\u73af\u5883+\u6d4b\u8bd5\u8f6f\u4ef6=\u6d4b\u8bd5\u7ed3\u679c\u201d\u7684\u6a21\u5f0f\u3002\u901a\u8fc7\u5404\u79cd\u5404\u6837\u7684\u6d4b\u8bd5\u5361\u548c\u5149\u6e90\uff0c\u5728\u5b9e\u9a8c\u5ba4\u4e2d\u6a21\u62df\u5404\u79cd\u73af\u5883\uff0c\u518d\u628a\u6210\u50cf\u7ed3\u679c\u8f93\u5165\u8f6f\u4ef6\u7cfb\u7edf\uff0c\u7531\u7cfb\u7edf\u81ea\u52a8\u5206\u6790\uff0c\u6700\u540e\u5f97\u51fa\u7ed3\u679c\u3002<\/p>\n

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\"\u56fe\u50cf\u8d28\u91cf\u8bc4\u4f30\u7b97\u6cd5_\u8bc4\u4ef7\u56fe\u50cf\u8d28\u91cf\u7684\u4e09\u8981\u7d20<\/p>\n

\u9664\u4e86\u5149\u6e90\uff0c\u6d4b\u8bd5\u5361\u4e5f\u662f\u975e\u5e38\u91cd\u8981\u7684\u6d4b\u8bd5\u7528\u5177\u3002\u9488\u5bf9\u4e0d\u540c\u7684\u6d4b\u8bd5\u9879\u76ee\uff0c\u6d4b\u8bd5\u5361\u4e5f\u662f\u5404\u6709\u4e0d\u540c\uff0c\u6709\u7684\u53ef\u4ee5\u6d4b\u8bd5\u5206\u8fa8\u7387\uff0c\u6709\u7684\u53ef\u4ee5\u6d4b\u8bd5MTF\uff0c\u6709\u7684\u53ef\u4ee5\u6d4b\u8bd5\u8272\u5dee\u2026\u2026ISO 12233\u6d4b\u8bd5\u5361\u662f\u6d4b\u8bd5\u955c\u5934\u5206\u8fa8\u7387\u6700\u6743\u5a01\u6d4b\u5b9a\u65b9\u6cd5\uff0c\u4e5f\u662f\u56fd\u9645MTF\u6210\u50cf\u66f2\u7ebf\u56fe\u548c\u955c\u5934\u8bc4\u4f30\u7684\u4e3b\u8981\u4f9d\u636e\u3002<\/p>\n

\"\u56fe\u50cf\u8d28\u91cf\u8bc4\u4f30\u7b97\u6cd5_\u8bc4\u4ef7\u56fe\u50cf\u8d28\u91cf\u7684\u4e09\u8981\u7d20<\/p>\n

\u6709\u4eba\u975e\u5e38\u597d\u5947\uff0c\u4e3a\u4ec0\u4e48\u5f71\u50cf\u8d28\u91cf\u8bc4\u6d4b\u9700\u8981\u51c6\u5907\u8fd9\u4e48\u591a\u7684\u6d4b\u8bd5\u7528\u5177\uff0c\u51c6\u5907\u5c11\u4e00\u4e9b\u6d4b\u8bd5\u5361\u3001\u5149\u6e90\u4e0d\u884c\u5417\uff1f<\/p>\n

\u6211\u4eec\u8981\u77e5\u9053\uff0c\u6211\u4eec\u51c6\u5907\u5404\u79cd\u6d4b\u8bd5\u5361\u548c\u5149\u6e90\u662f\u4e3a\u4e86\u6a21\u62df\u5404\u79cd\u5149\u7167\u73af\u5883\uff0c\u4ee5\u53ca\u6d4b\u8bd5\u4ea7\u54c1\u5728\u8fd9\u4e9b\u5149\u7167\u73af\u5883\u4e0b\u7684\u8868\u73b0\u3002\u6211\u4eec\u6c38\u8fdc\u4e5f\u65e0\u6cd5\u731c\u5230\u7528\u6237\u4f1a\u5728\u4ec0\u4e48\u73af\u5883\u4e0b\u4f7f\u7528\u6211\u4eec\u7684\u4ea7\u54c1\uff0c\u5c31\u5982\u4e4b\u524d\u7279\u65af\u62c9\u6ca1\u6709\u8003\u8651\u5230\u7528\u6237\u4f1a\u5728\u9633\u5149\u707f\u70c2\u7684\u65f6\u5019\u9047\u5230\u4e00\u8f86\u767d\u8272\u5361\u8f66\uff0c\u6444\u50cf\u5934\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\u5931\u7075\u800c\u53d1\u751f\u4e86\u7b2c\u4e00\u8d77\u65e0\u4eba\u9a7e\u9a76\u8f66\u7978\u3002\u6240\u4ee5\uff0c\u6211\u4eec\u80fd\u505a\u5230\u7684\u662f\u5c3d\u53ef\u80fd\u6d4b\u8bd5\u4ea7\u54c1\u5728\u5404\u79cd\u73af\u5883\u4e0b\u7684\u8868\u73b0\uff0c\u4e89\u53d6\u8ba9\u4ea7\u54c1\u5728\u5404\u79cd\u73af\u5883\u4e0b\u90fd\u8868\u73b0\u6b63\u5e38\u3002<\/p>\n

 <\/p>\n

\u4e8c\u3001IQA\u8bc4\u4f30\u6307\u6807<\/h2>\n

\u73b0\u5728\u8fd8\u4e0d\u77e5\u9053\u9664\u4e86\u8089\u773c\u4e4b\u5916\u7684\u597d\u529e\u6cd5\uff0c\u53ea\u80fd\u5148\u6765\u5217\u4e3e\u4e00\u4e0b\u4f20\u7edfIQA\u7684\u4e00\u4e9b\u8bc4\u4f30\u6307\u6807\uff08\u4e3b\u8981\u53c2\u8003\u8bba\u6587\uff1a\u300a\u65e0\u53c2\u8003\u56fe\u50cf\u8d28\u91cf\u8bc4\u4ef7\u7efc\u8ff0\u300b\uff09\uff1a 
.<\/p>\n

1\u3001MOS\u3001DMOS<\/h3>\n

\u56fe\u50cf\u8d28\u91cf\u8bc4\u4ef7\u53ef\u4ee5\u5206\u4e3a\u4e3b\u89c2\u8bc4\u4ef7\u65b9\u6cd5\u548c\u5ba2\u89c2\u8bc4\u4ef7\u65b9\u6cd5, <\/p>\n

\u4e3b\u89c2\u8bc4\u4ef7\u7531\u89c2\u5bdf\u8005\u5bf9\u56fe\u50cf\u8d28\u91cf\u8fdb\u884c\u4e3b\u89c2\u8bc4\u5206, \u4e00\u822c\u91c7\u7528\u5e73\u5747\u4e3b\u89c2\u5f97\u5206(Mean opin-ion score, MOS) \u6216\u5e73\u5747\u4e3b\u89c2\u5f97\u5206\u5dee\u5f02(Di\u00aeerential mean opinion score, DMOS) (\u5373\u4eba\u773c\u5bf9\u65e0\u5931\u771f\u56fe\u50cf\u548c\u6709\u5931\u771f\u56fe\u50cf\u8bc4\u4ef7\u5f97\u5206\u7684\u5dee\u5f02) <\/p>\n

Subjective quality assessment can be applied by visual perception or mean opinion score (MOS), which has been used in ITU-T p.910, a standard in multimedia services. Visual perception is predicated on the observers\u2019 perception without a numerical quantification. MOS is defined as the average of the quality values ranging from1 to 5that are obtained from observers.<\/p>\n

.\"\u56fe\u50cf\u8d28\u91cf\u8bc4\u4f30\u7b97\u6cd5_\u8bc4\u4ef7\u56fe\u50cf\u8d28\u91cf\u7684\u4e09\u8981\u7d20<\/p>\n

 <\/p>\n

\u7f3a\u70b9\uff1a<\/h4>\n

         \u8017\u8d39\u4eba\u529b\uff0c\u4e0d\u662f\u81ea\u52a8\u7684\uff0c\u4e0d\u5229\u4e8e\u8c03\u6574\u53c2\u6570\u3002<\/p>\n

\u4f18\u70b9\uff1a<\/h4>\n

        \u6839\u636e\u4eba\u773c\u7684\u611f\u77e5\uff0c\u76f4\u89c2\u5e76\u80fd\u8f83\u7cbe\u786e\u5730\u8bc4\u4ef7\u56fe\u7247\u7684\u8d28\u91cf<\/p>\n

 <\/p>\n

2\u3001\u5747\u65b9\u6839\u8bef\u5dee(Root mean squared error, RMSE)<\/h3>\n

\u5747\u65b9\u6839\u8bef\u5dee\u6bd4\u8f83\u7b97\u6cd5\u8bc4\u4ef7\u503c\u4e0e\u4eba\u773c\u4e3b\u89c2\u6253\u5206\u4e4b\u95f4\u7684\u7edd\u5bf9\u8bef\u5dee, \u8861\u91cf\u7b97\u6cd5\u9884\u6d4b\u7684\u51c6\u786e\u6027 
.<\/p>\n

3\u3001\u7ebf\u6027\u76f8\u5173\u7cfb\u6570(Linear correlation coe\u00b1- cient, LCC), \u4e5f\u79f0\u4e3a\u76ae\u5c14\u900a(Pearson) \u7ebf\u6027\u76f8\u5173 \u7cfb\u6570<\/h3>\n

\u7ebf\u6027\u76f8\u5173\u7cfb\u6570\u63cf\u8ff0\u7b97\u6cd5\u8bc4\u4ef7\u503c\u4e0e\u4eba\u773c\u4e3b\u89c2\u6253\u5206\u4e4b\u95f4\u7684\u76f8\u5173\u6027, \u4e5f\u8861\u91cf\u4e86\u7b97\u6cd5\u9884\u6d4b\u7684\u51c6\u786e\u6027. 
.<\/p>\n

4\u3001Spearman \u79e9\u76f8\u5173\u7cfb\u6570(Spearman0s rank ordered correlation coe\u00b1cient, SROCC)<\/h3>\n

Spearman \u79e9\u7ebf\u6027\u76f8\u5173\u7cfb\u6570\u8861\u91cf\u7b97\u6cd5\u9884\u6d4b\u7684\u5355\u8c03\u6027(Monotonicity). 
.<\/p>\n

5\u3001Kendall \u79e9\u76f8\u5173\u7cfb\u6570(Kendall rank order correlation coe\u00b1cient, KROCC)<\/h3>\n

Kendall \u79e9\u7ebf\u6027\u76f8\u5173\u7cfb\u6570\u4e5f\u8861\u91cf\u4e86\u7b97\u6cd5\u9884\u6d4b\u7684\u5355\u8c03\u6027. 
.<\/p>\n

6\u3001\u79bb\u51fa\u7387(Outlier ratio, OR)<\/h3>\n

\u79bb\u51fa\u7387\u8868\u793a\u8d85\u51fa\u4e3b\u89c2\u5f97\u5206\u00a72 \u500d\u6807\u51c6\u5dee(\u5b58\u5728\u591a\u4e2a\u89c2\u5bdf\u8005\u7684\u4e3b\u89c2\u5f97\u5206\u65f6) \u7684\u6837\u672c\u6570\u767e\u5206\u6bd4 
.<\/p>\n

\u5ba2\u89c2\u8bc4\u4ef7\u65b9\u6cd5\uff1a\u5bf9\u91cd\u5efa\u56fe\u50cf\u4e0e\u539f\u59cb\u56fe\u50cf\u7684\u5dee\u522b\u8fdb\u884c\u5b9a\u91cf\u7684\u8ba1\u7b97\u3002<\/p>\n

\u65b9\u6cd5\u4e3b\u8981\u5206\u4e3a\u4e24\u7c7b\uff1a\u76f8\u5bf9\u6574\u4e2a\u56fe\u50cf  \u3001 \u4e0e\u4e3b\u89c2\u89c6\u89c9\u611f\u77e5\u76f8\u5173\u3002<\/p>\n

\u76f8\u5bf9\u6574\u4e2a\u56fe\u50cf<\/h2>\n

\u76f8\u5bf9\u6574\u4e2a\u56fe\u50cf\u7684\u65b9\u6cd5\u6709\uff1a<\/p>\n

    \n
  • 1:\u5cf0\u503c\u4fe1\u566a\u6bd4PSNR(Peak Signal to Noise Ratio)\uff0c<\/li>\n
  • 2\uff1a\u7ed3\u6784\u76f8\u4f3c\u6027SSIM\uff08structural similarity\uff09 ,<\/li>\n
  • 3:\u5747\u65b9\u8bef\u5deeMSE(mean square error)\uff0c<\/li>\n
  • 4: RMSE(root mean square error)\uff0c<\/li>\n
  • 5: corss-correlation ;<\/li>\n<\/ul>\n

    ------------------------------------------------------------<\/p>\n

    PSNR:<\/p>\n

    \u4f18\u70b9\uff1a\u7b97\u6cd5\u7b80\u5355\uff0c\u68c0\u67e5\u7684\u901f\u5ea6\u5feb\u3002<\/p>\n

    \u7f3a\u70b9\uff1a\u5448\u73b0\u7684\u5dee\u5f02\u503c\u4e0e\u4eba\u7684\u4e3b\u89c2\u611f\u53d7\u4e0d\u6210\u6bd4\u4f8b\u3002<\/p>\n

    -------------------------------------------------------------<\/p>\n

    SSIM:<\/p>\n

    \u4f18\u70b9\uff1a\u6539\u8fdb\u4e86PSNR\u7684\u7f3a\u70b9\u3002<\/p>\n

    \u7f3a\u70b9\uff1a\u7ed3\u6784\u76f8\u4f3c\u6027\u6307\u6807\u6709\u5176\u9650\u5236\uff0c\u5bf9\u4e8e\u5f71\u50cf\u51fa\u73b0\u4f4d\u79fb\u3001\u7f29\u653e\u3001\u65cb\u8f6c\uff08\u7686\u5c5e\u4e8e\u975e\u7ed3\u6784\u6027\u7684\u5931\u771f\uff09\u7684\u60c5\u51b5\u65e0\u6cd5\u6709\u6548\u7684\u8fd0\u4f5c\u3002\u4e3a\u89e3\u51b3\u6b64\u95ee\u9898\uff0c\u53e6\u5df2\u53d1\u5c55\u51fa\u5728\u5c0f\u6ce2\u57df\u8fdb\u884c\u8fd0\u7b97\u7684\u7ed3\u6784\u76f8\u4f3c\u6027\u6307\u6807\uff0c\u79f0\u4f5c\u590d\u5c0f\u6ce2\u7ed3\u6784\u76f8\u4f3c\u6027\u6307\u6807[8]\uff08\u82f1\u6587\uff1acomplex wavelet SSIM\uff0cCW-SSIM\uff09\u3002<\/p>\n

    \u8ba1\u7b97\u516c\u5f0f\u4e0e\u539f\u7406\uff1a\u53c2\u8003\u7ef4\u57fa\u767e\u79d1 \u8bcd\u6761\u00a0\u7ed3\u6784\u76f8\u4f3c\u6027<\/p>\n

    \u6e90\u7801\uff1aopencv\u6e90\u7801\u53ef\u53c2\u8003 opencv\u6559\u7a0b \uff1a\u00a0opencv\u7684\u89c6\u9891\u8f93\u5165\u548c\u76f8\u4f3c\u5ea6\u6d4b\u91cf<\/p>\n

    --------------------------------------------------------------------------------------------------<\/p>\n

     <\/p>\n

    --------------------------------------------------------------<\/p>\n

    MSE | PSNR | SNR | MAE \u7684 \u8ba1\u7b97\u65b9\u6cd5\uff1a<\/p>\n

    ---------------------------------------------------<\/p>\n

                        \"\u56fe\u50cf\u8d28\u91cf\u8bc4\u4f30\u7b97\u6cd5_\u8bc4\u4ef7\u56fe\u50cf\u8d28\u91cf\u7684\u4e09\u8981\u7d20<\/p>\n

    \u7f3a\u70b9\uff1a<\/p>\n

    \u6c42\u5f97\u7684\u7ed3\u679c\u5e38\u5e38\u4e0e\u4eba\u4eec\u7684\u4e3b\u89c2\u89c6\u89c9\u6548\u679c\u4e0d\u4e00\u81f4\uff0c\u8fd9\u662f\u56e0\u4e3a\u5747\u65b9\u8bef\u5dee\u3001\u5cf0\u503c\u4fe1\u566a\u6bd4\u548c\u4fe1\u53f7\u566a\u58f0\u6bd4\u7b49\u90fd\u662f\u4ece\u6574\u4f53\u4e0a\u53cd\u6620\u539f\u59cb\u56fe\u50cf\u548c\u91cd\u5efa\u56fe\u50cf\u7684\u5dee\u522b\uff0c\u5e76\u4e0d\u80fd\u53cd\u6620\u4e00\u5e45\u56fe\u50cf\u4e2d\u5c11\u6570\u50cf\u7d20\u70b9\u6709\u8f83\u5927\u7070\u5ea6\u5dee\u522b\u548c\u8f83\u591a\u50cf\u7d20\u70b9\u6709\u8f83\u5c0f\u5dee\u522b\u7b49\u5404\u79cd\u60c5\u51b5\u3002\u663e\u7136\uff0c\u5ba2\u89c2\u8d28\u91cf\u8bc4\u4ef7\u91c7\u7528\u4ee5\u4e0a\u5404\u5f0f\u662f\u5bf9\u56fe\u50cf\u4e2d\u6240\u6709\u7684\u50cf\u7d20\u70b9\u540c\u6837\u5bf9\u5f85\u7684\uff0c\u4e0d\u80fd\u5168\u9762\u53cd\u6620\u4eba\u773c\u7684\u89c6\u89c9\u7279\u6027\u3002<\/p>\n

    \u4e0e\u4e3b\u89c2\u89c6\u89c9\u611f\u77e5\u76f8\u5173<\/h4>\n

    \u4e0e\u4e3b\u89c2\u89c6\u89c9\u611f\u77e5\u76f8\u5173\u7684\u65b9\u6cd5\u6709\uff1a universal image quality index\uff08UIQI\uff09\uff0cSSIM,VIF,FSI\u3002\uff08\u4e0a\u8ff0\u65b9\u6cd5\u53ef\u5728reference2\u4e2d\u8bba\u6587\u4e2d\u627e\u5230\uff09<\/p>\n

     <\/p>\n

    ============================================================================================================<\/p>\n

    \u65b9\u6cd5\u7684\u5bf9\u6bd4<\/h3>\n

    \u9488\u5bf9\u4e8e image super-resolution 8\u79cd\u65b9\u6cd5\u8861\u91cf\u56fe\u7247super-resolution\u4e4b\u540e\u7684\u8d28\u91cf\u7684\u5bf9\u6bd4<\/p>\n

    \"\u56fe\u50cf\u8d28\u91cf\u8bc4\u4f30\u7b97\u6cd5_\u8bc4\u4ef7\u56fe\u50cf\u8d28\u91cf\u7684\u4e09\u8981\u7d20<\/p>\n

     <\/p>\n

    IFC > NQM > WPSNR > MSSSIM > SSIM > UIQI > PSNR >VIF <\/p>\n

    \u6700\u597d\u7684\u65b9\u6cd5\u4e3aIFC<\/p>\n

    \u539f\u56e0\uff1a<\/p>\n

    1\uff1athe IFC metric is designed to evaluate the loss of image information so that it extracts wavelet features with fo cus on high- frequency details rather than low-frequency comp onents. This me tric matches human p erception well as visual p erception is more sensitive to high-frequency details of SR images rather than low-frequency components. <\/p>\n

    2\uff1aSecond, the IFC metric is develop ed based on natural scene statistics using the Gaussian scale mixtures [37] and the BSD200 dataset contains numerous such images.<\/p>\n

    \n

    \u4e09\u3001\u56fe\u50cf\u8d28\u91cf\u68c0\u6d4b\u65b9\u5f0f<\/h2>\n

    \u672c\u7ae0\u53ea\u662f\u7b80\u5355\u6765\u8bf4\u8bf4\u4f20\u7edf\u7684\uff0c\u73b0\u5728\u5e76\u4e0d\u77e5\u9053\u5982\u4f55\u5bf9\u56fe\u50cf\u5185\u5bb9\u8d28\u91cf\u8fdb\u884c\u68c0\u6d4b\u7684\u65e0\u76d1\u7763\u529e\u6cd5\u3002 
    .<\/p>\n

    1\u3001\u5168\u3001\u534a\u53c2\u8003\u65b9\u6cd5<\/h3>\n

    \u56fe\u50cf\u7684\u67d0\u4e9b\u7279\u5f81\u4e0e\u539f\u59cb\u56fe\u50cf\u7684\u76f8\u540c\u7279\u5f81\u8fdb\u884c\u6bd4\u8f83, \u6bd4\u5982\u5c0f\u6ce2\u53d8\u6362\u7cfb\u6570\u7684\u6982\u7387\u5206\u5e03\u3001\u7efc\u5408\u591a\u5c3a\u5ea6\u51e0\u4f55\u5206\u6790\u3001\u5bf9\u6bd4\u5ea6\u654f\u611f\u51fd\u6570\u548c\u53ef\u89c9\u5bdf\u7070\u5ea6\u5dee\u5f02\u7279\u5f81 \u7b49. \u5176\u76f8\u5e94\u7684\u5e94\u7528\u9886\u57df\u5305\u62ec\u89c6\u9891\u4f20\u8f93\u4e2d\u7684\u6570\u5b57\u6c34\u5370\u9a8c\u8bc1\u3001\u5229\u7528\u526f\u901a\u9053\u8fdb\u884c\u89c6\u9891\u8d28\u91cf\u76d1\u63a7\u4e0e\u7801\u6d41\u7387\u63a7\u5236\u7b49. 
    .<\/p>\n

    2\u3001\u76f2\u56fe\u50cf\u8d28\u91cf(Blind image quality, BIQ)<\/h3>\n

    \u8bc4\u4ef7\u65b9\u6cd5, \u5219\u5b8c\u5168\u65e0\u9700\u53c2\u8003\u56fe\u50cf, \u6839\u636e\u5931\u771f\u56fe\u50cf\u7684\u81ea\u8eab\u7279\u5f81\u6765\u4f30\u8ba1\u56fe\u50cf\u7684\u8d28\u91cf. \u6709\u4e9b\u65b9\u6cd5\u662f\u9762\u5411\u7279\u5b9a\u5931\u771f\u7c7b\u578b\u7684, \u5982\u9488\u5bf9\u6a21\u7cca\u3001\u566a\u58f0\u3001\u5757\u72b6\u6548\u5e94\u7684\u4e25\u91cd\u7a0b\u5ea6\u8fdb\u884c\u8bc4\u4ef7; \u6709\u4e9b\u65b9\u6cd5\u5148\u8fdb\u884c\u5931\u771f\u539f\u56e0\u5206\u7c7b, \u518d\u8fdb\u884c\u5b9a\u91cf\u8bc4\u4ef7; \u800c\u6709\u4e9b\u65b9\u6cd5\u5219\u8bd5\u56fe\u540c\u65f6\u8bc4\u4ef7\u4e0d\u540c\u5931\u771f\u7c7b\u578b\u7684\u56fe\u50cf. \u65e0\u53c2\u8003\u65b9\u6cd5\u6700\u5177\u5b9e\u7528\u4ef7\u503c, \u6709\u7740\u975e\u5e38\u5e7f\u6cdb\u7684\u5e94\u7528\u8303\u56f4. 
    .<\/p>\n

    3\u3001\u673a\u5668\u5b66\u4e60\u7684\u56fe\u50cf\u8d28\u91cf\u8bc4\u4ef7<\/h3>\n

    \uff081\uff09SVM \uff0b SVR 
    \u7b97\u6cd5\u5219\u91c7\u7528\u4e24\u6b65\u65b9\u6848, \u5148\u7528SVM \u8fdb\u884c\u5931\u771f\u7c7b\u578b\u8bc6\u522b, \u8fdb\u800c\u5bf9\u7279\u5b9a\u5931\u771f\u7c7b\u578b\u5efa\u7acbSVR \u56de\u5f52\u5206\u6790\u6a21\u578b,\u6211\u4eec\u79f0\u4e4b\u4e3aSVM \uff0b SVR \u6a21\u578b. 
    \uff082\uff09GGD 
    Moorthy \u548cBovik\u7684\u76f2\u56fe\u50cf\u8d28\u91cf\u6307\u6570(Blind image quality index, BIQI) \u5206\u4e24\u6b65\u5bf9\u56fe\u50cf\u8fdb\u884c\u8bc4\u4ef7, \u5148\u91c7\u7528\u5c0f\u6ce2\u5206\u89e3\u7cfb\u6570\u7ecf\u5e7f\u4e49\u9ad8\u65af\u5206\u5e03(Generalized Gaussian distribution, GGD) \u6a21\u578b\u62df\u5408\u5f97\u5230\u7684\u53c2\u6570\u4f5c\u4e3a\u7279\u5f81, \u7531SVM \u5206\u7c7b\u5f97\u5230\u5f53\u524d\u56fe\u50cf\u5c5e\u4e8e\u6bcf\u4e2a\u7c7b\u7684\u6982\u7387, \u518d\u91c7\u7528SVR \u5bf9\u5404\u4e2a\u9000\u5316\u7c7b\u578b\u8ba1\u7b97\u56fe\u50cf\u8d28\u91cf\u6307\u6807\u503c, \u6700\u540e\u6839\u636e\u6982\u7387\u52a0\u6743\u5f97\u5230\u603b\u7684\u8d28\u91cf\u8bc4\u4ef7\u6307\u6807; \u5728\u540e\u7eed\u7684\u57fa\u4e8e\u5931\u771f\u8fa8\u8bc6\u7684\u56fe\u50cf\u771f 
    \u5b9e\u6027\u548c\u5b8c\u6574\u6027\u8bc4\u4ef7\u3002 
    .<\/p>\n

    4\u3001\u57fa\u4e8e\u6982\u7387\u6a21\u578b\u7684\u65b9\u6cd5<\/h3>\n

    \u8fd9\u7c7b\u65b9\u6cd5\u9996\u5148\u5efa\u7acb\u56fe\u50cf\u7279\u5f81\u4e0e\u56fe\u50cf\u8d28\u91cf\u4e4b\u95f4\u7684\u7edf\u8ba1\u6982\u7387\u6a21\u578b, \u5927\u591a\u91c7\u7528\u591a\u53d8\u91cf\u9ad8\u65af\u5206\u5e03\u63cf\u8ff0\u6982\u7387\u5206\u5e03. \u5bf9\u5f85\u8bc4\u4ef7\u56fe\u50cf, \u63d0\u53d6\u7279\u5f81\u540e\u6839\u636e\u6982\u7387\u6a21\u578b\u8ba1\u7b97\u6700\u5927\u540e\u9a8c\u6982\u7387\u7684\u56fe\u50cf\u8d28\u91cf, \u6216\u6839\u636e\u4e0e\u6982\u7387\u6a21\u578b\u7684\u5339\u914d\u7a0b\u5ea6(\u5982\u7279\u5f81\u95f4\u7684\u8ddd\u79bb) \u4f30\u8ba1\u56fe\u50cf\u8d28\u91cf.<\/p>\n

    \u5728\u5fb7\u514b\u8428\u65af\u5927\u5b66\u5965\u65af\u6c40\u5206\u6821\u7684Mittal \u7b49 \u63d0\u51fa\u7684\u81ea\u7136\u56fe\u50cf\u8d28\u91cf\u8bc4\u4ef7(Natural image quality evaluator, NIQE) \u7b97\u6cd5\u4e2d, \u65e0\u9700\u5229\u7528\u4eba\u773c\u8bc4\u5206\u7684\u5931\u771f\u56fe\u50cf\u8fdb\u884c\u8bad\u7ec3, \u5728\u8ba1\u7b97\u5176\u5c40\u90e8MSCN \u5f52\u4e00\u5316\u56fe\u50cf\u540e, \u6839\u636e\u5c40\u90e8\u6d3b\u6027\u9009\u62e9\u90e8\u5206\u56fe\u50cf\u5757\u4f5c\u4e3a\u8bad\u7ec3\u6570\u636e, \u4ee5\u5e7f\u4e49\u9ad8\u65af\u6a21\u578b\u62df\u5408\u5f97\u5230\u6a21\u578b\u53c2\u6570\u4f5c\u4e3a\u7279\u5f81, \u91c7\u7528\u591a\u53d8\u91cf\u9ad8\u65af\u6a21\u578b\u63cf\u8ff0\u8fd9\u4e9b\u7279\u5f81, \u8bc4\u4ef7\u8fc7\u7a0b\u4e2d\u5229\u7528\u5f85\u8bc4\u4ef7\u56fe\u50cf\u7279\u5f81\u6a21\u578b\u53c2\u6570\u4e0e\u9884\u5148\u5efa\u7acb\u7684\u6a21\u578b\u53c2\u6570\u4e4b\u95f4\u7684\u8ddd\u79bb\u6765\u786e\u5b9a\u56fe\u50cf\u8d28\u91cf<\/p>\n

    Abdalmajeed \u548cJiao\u5728\u5bf9\u56fe\u50cf\u8fdb\u884c\u5c40\u90e8MSCN \u5f52\u4e00\u5316\u540e, \u57fa\u4e8e\u97e6\u4f2f\u5206\u5e03\u63d0\u53d6\u81ea\u7136\u56fe\u50cf\u7edf\u8ba1\u7279\u5f81, \u5e76\u4ee5\u591a\u53d8\u91cf\u9ad8\u65af\u5206\u5e03\u63cf\u8ff0\u5b83\u7684\u6982\u7387\u5206\u5e03, \u8bc4\u65f6\u8ba1\u7b97\u5f85\u8bc4\u4ef7\u56fe\u50cf\u7279\u5f81\u4e0e\u65e0\u5931\u771f\u56fe\u50cf\u7edf\u8ba1\u6a21\u578b\u7684\u8ddd\u79bb\u4f5c\u4e3a\u56fe\u50cf\u8d28\u91cf\u8bc4\u4ef7\u5ea6\u91cf. \u6839\u636e\u6982\u7387\u5efa\u6a21\u662f\u4e00\u79cd\u57fa\u4e8e\u5927\u91cf\u6837\u672c\u7684\u7edf\u8ba1\u65b9\u6cd5, \u6982\u7387\u6570\u5b66\u6a21\u578b\u7684\u9009\u62e9\u548c\u6837\u672c\u91cf\u7684\u5927\u5c0f\u662f\u5f71\u54cd\u6027\u80fd\u7684\u5173\u952e, \u73b0\u6709\u65b9\u6cd5\u5927\u90fd\u57fa\u4e8e\u591a\u53d8\u91cf\u9ad8\u65af\u6a21\u578b\u8fdb\u884c\u6982\u7387\u5efa\u6a21, \u4e3b\u8981\u662f\u4e3a\u4e86\u65b9\u4fbf\u5efa\u6a21. \u8003\u8651\u5230\u8868\u5f81\u56fe\u50cf\u8d28\u91cf\u7684\u7279\u5f81\u7ef4\u5ea6\u5f88\u9ad8, \u590d\u6742\u7684\u6a21\u578b\u5c06\u9700\u8981\u66f4\u591a\u7684\u6570\u636e\u91cf, \u8fd9\u7c7b\u65b9\u6cd5\u53ea\u6709\u5f53\u6570\u636e\u91cf\u8f83\u5927\u65f6\u624d\u53ef\u80fd\u53d6\u5f97\u8f83\u597d\u7684\u6548\u679c\u3002 
    .<\/p>\n

    5\u3001\u795e\u7ecf\u7f51\u7edc\u7684\u65b9\u6cd5<\/h3>\n

    \u8fd9\u7c7b\u65b9\u6cd5\u5148\u63d0\u53d6\u4e00\u5b9a\u7684\u56fe\u50cf\u53d8\u6362\u57df\u6216\u7a7a\u95f4\u7279\u5f81, \u518d\u57fa\u4e8e\u5df2\u77e5\u8d28\u91cf\u6570\u636e\u8bad\u7ec3\u4e00\u4e2a\u795e\u7ecf\u7f51\u7edc\u56de\u5f52\u5206\u6790\u6a21\u578b, \u7531\u56fe\u50cf\u7279\u5f81\u9884\u6d4b\u56fe\u50cf\u8d28\u91cf. 
    Kang \u7b49\u91c7\u7528\u5377\u79ef\u795e\u7ecf\u7f51\u7edc(Convolutionalneural networks, CNN) \u5c06\u7279\u5f81\u63d0\u53d6\u548c\u56de\u5f52\u5206\u6790\u878d\u5165\u540c\u4e00\u4e2a\u7f51\u7edc\u4e2d, \u7f51\u7edc\u5305\u62ec5 \u5c42, \u56fe\u50cf\u7ecf\u5c40\u90e8MSCN\u5f52\u4e00\u5316\u540e\u4ee532 \u00a3 32 \u5b50\u5757\u8f93\u5165\u7f51\u7edc, \u7b2c\u4e00\u5c42\u5377\u79ef\u5c42\u753150 \u4e2a\u6ee4\u6ce2\u5668\u63d0\u53d6\u7279\u5f81, \u7b2c\u4e8c\u5c42\u8fdb\u884c\u6700\u5927\u6700\u5c0f\u9009\u62e9, \u540e\u9762\u4e24\u5c42\u4e3a800 \u8282\u70b9\u7684\u5168\u8fde\u63a5\u7f51\u7edc, \u6700\u540e\u4e00\u5c42\u4e3a\u5355\u4e2a\u8282\u70b9\u8f93\u51fa\u56fe\u50cf\u8d28\u91cf\u3002<\/p>\n

    Hou \u7b49\u4e5f\u91c7\u7528\u5177\u67095 \u5c42\u7f51\u7edc\u7ed3\u6784\u7684\u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\u8fdb\u884c\u56fe\u50cf\u8d28\u91cf\u8bc4\u4ef7,\u7efc\u5408\u7279\u5f81\u63d0\u53d6\u3001\u5206\u7c7b\u3001\u540e\u9a8c\u6982\u7387\u8ba1\u7b97\u7b49\u529f\u80fd\u4e3a\u4e00\u4f53,\u75313 \u7ea7\u5c0f\u6ce2\u53d8\u6362\u7ec6\u8282\u7279\u5f81\u4e3a\u8f93\u5165, \u8bad\u7ec3\u8fc7\u7a0b\u5148\u91c7\u7528\u53d7\u9650\u6ce2\u5c14\u5179\u66fc\u673a(Restricted Boltzmann machine,RBM) \u8fdb\u884c\u5c42\u95f4\u5b66\u4e60, \u518d\u91c7\u7528\u53cd\u5411\u4f20\u9012\u7b97\u6cd5\u8fdb\u884c\u7cbe\u7ec6\u8c03\u6574. \u8fd9\u4e24\u79cd\u7b97\u6cd5\u7684\u5b9e\u9a8c\u7ed3\u679c\u5747\u660e\u663e\u4f18\u4e8e\u5176\u4ed6\u65e0\u53c2\u8003\u7b97\u6cd5, \u751a\u81f3\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\u4f18\u4e8e\u5168\u53c2\u8003\u7b97\u6cd5\u4e2d\u8f83\u597d\u7684VIF<\/p>\n","protected":false},"excerpt":{"rendered":"\u56fe\u50cf\u8d28\u91cf\u8bc4\u4f30\u7b97\u6cd5_\u8bc4\u4ef7\u56fe\u50cf\u8d28\u91cf\u7684\u4e09\u8981\u7d20\u4e00\u3001\u6982\u8ff0\u5728\u56fe\u50cf\u4fe1\u606f\u6280\u672f\u88ab\u5e7f\u6cdb\u5e94\u7528\u7684\u60c5\u51b5\u4e0b\uff0c\u5bf9\u56fe\u50cf\u8d28\u91cf\u7684\u8bc4\u4f30\u53d8\u6210\u4e00\u4e2a\u5e7f\u6cdb\u800c\u57fa\u672c\u7684\u95ee\u9898","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"_links":{"self":[{"href":"https:\/\/mushiming.com\/wp-json\/wp\/v2\/posts\/8493"}],"collection":[{"href":"https:\/\/mushiming.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mushiming.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mushiming.com\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/mushiming.com\/wp-json\/wp\/v2\/comments?post=8493"}],"version-history":[{"count":0,"href":"https:\/\/mushiming.com\/wp-json\/wp\/v2\/posts\/8493\/revisions"}],"wp:attachment":[{"href":"https:\/\/mushiming.com\/wp-json\/wp\/v2\/media?parent=8493"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mushiming.com\/wp-json\/wp\/v2\/categories?post=8493"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mushiming.com\/wp-json\/wp\/v2\/tags?post=8493"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}